1. Field of the Invention
The present invention relates to a gain-shape vector quantization apparatus, and particularly to a gain-shape vector quantization apparatus for compressing the data of speech signals.
In recent years, a vector quantization system for compressing the data of speech signals yet maintaining the quality thereof has been employed for communication systems within companies and for digital mobile wireless systems or the like. As is well known, the vector quantization system consists of passing signal vectors of a code book through a synthesis filter to reproduce signals, and evaluating error electric powers between the reproduced signals and the input speech signals in order to determine the index of a signal vector having the smallest error. Among a variety of such vector quantization systems, attention has now been given particularly to a gain-shape (amplitude-phase) vector quantization system used as a high quality speech coding method.
2. Description of the Related Art
FIG. 1 illustrates the constitution of a conventional gain-shape vector quantization apparatus according to which a shape vector (phase) is selected out of shape vectors obtained by normalizing electric power of a plurality of vectors that constitute a code book 11 having a size S and a dimension (or order) L, and multiplied by a gain (amplitude) through a variable gain circuit 12 to separate an amplitude component from a phase component. Then, a signal X is reproduced through a synthesis filter 13 that includes a pitch synthesis filter 13a and an LPC (linear predictive coding) synthesis filter 13b. The synthesis filter 13 has a transfer function H(Z). An error E between the reproduced signal X and the input signal A is evaluated by an evaluation unit 14, whereby a shape vector Ck in the code book 11 is newly selected such that the error E becomes the smallest according to the following equations (1) and (2), ##EQU1## Furthermore, the gain g for a shape vector is determined based on the error electric power of E, the gain being calculated for each shape vector.
Then, the index of the shape vector of the code book 11, gain of the variable gain circuit 12, pitch delay of pitch prediction coefficients the pitch synthesis filter 13a, and LPC coefficient of when the input voice is analyzed through an LPC analyzer 15, which are obtained as described above, are transmitted to compress the speech data. According to such a conventional gain-shape vector quantization system, however, there exists only one code book, and only one shape vector is selected from the code book by the evaluation unit resulting in an increase in the quantization distortion (quantize error) and making it difficult to maintain quality of the reproduced speech.
Such a quantization distortion can be decreased by increasing the number of code vectors (shape vectors) included in the code book and by increasing the dimension of the code book. However, the amount of operation for finding an optimum shape vector increases, too, with the increase in the size of the code book, and increased memory is required for storing the shape vectors, posing a serious hindrance for realizing the hardware and causing the amount of shape vector index transmission to increase.
When the size of the code book is decreased to quicken the speed of operation, on the other hand, the reproduced speech loses quality due to quantization error.